Download PDFOpen PDF in browserCurrent versionPromoting Archival Engagement Through Computational InterventionsEasyChair Preprint 8443, version 114 pages•Date: July 10, 2022AbstractThis paper illustrates how to design and implement an engaged computational archival framework that leverages big archival records in order to respond to social justice and reparations policy imperatives. The work touches on two of the conference themes: (1) how to handle histories of people whose lives were deeply impacted by public authorities, and (2) Archives as Big Data as a potential restorative strategy. Over the last few years Computational Archival Science (CAS) has emerged as a new discipline that explores the use and consequences of emerging methods and technologies around big data with archival practice and new forms of analysis and historical, social, scientific, and cultural research engagement with archives. Our paper presents a very timely case study focusing on the legacy of urban renewal in Asheville, North Carolina between 1965 and 1980, when housing policies were enacted that ultimately displaced and erased African American businesses and communities with traumatic and lasting effects. "Urban Renewal was a program created by the U.S. Federal Housing Act of 1949, with the intention of redeveloping areas of cities that were deemed blighted." The study discusses making community members the focus of archives, and designing new interfaces to tell human stories. We explore CAS in the context of reparation, truth and reconciliation based on an earlier project developed by the U. Maryland team. On March 15, 2022 a Reparations Commission was finally formed, with ten seats for appointments representing the areas of criminal justice, economic development, education, health care, and housing, and fifteen seats for residents of historically impacted African American neighborhoods. The authors of this paper believe this work serves as a model for other historical types of reparation that can benefit from CAS approaches. Keyphrases: Archival records, Archives as Big Data, Reparations, computational archival science, social memory, urban renewal
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